Binding mechanisms of Y and HREE sorption on birnessite: New insights into the formation and sustainable development of regolith-hosted REE deposits
Bibliographic record
Abstract
Abstract Regolith-hosted rare earth element (REE) deposits are the world’s primary source of heavy REEs (HREEs) critical to the global clean-energy transition. Previous studies suggested that REEs in regolith-hosted deposits are largely inherited from their parent granites. However, several HREE-dominated deposits occur in the weathering crusts of light REE (LREE)-enriched granites, where the mechanisms of REE fractionation remain poorly understood. Also, the conventional mining method of regolith-hosted REE deposits has limited efficiencies in REE recovery while causing enormous environmental contamination. Herein, we have investigated the distribution and speciation of Y and REEs in three representative regolith-hosted REE deposits (i.e., Gucheng and Shangyou, HREE-dominated; Renju, LREE-dominated) as well as Y-sorbed birnessite from batch experiments. Our results show that birnessite in all three deposits is a minor constituent but contains anomalously high concentrations of REEs and contributes to 25.3, 23.4, and 26.5% of the HREE contents of mineralized saprolites. Measured Y K-edge X–ray absorption spectroscopic data suggest that Y3+ (representing HREE3+) is adsorbed on birnessite as YO8 complexes in all three deposits but via different linkages: i.e., the bidentate corner-sharing mode in the HREE-dominated deposits but a mixture of both bidentate corner-sharing and edge-sharing modes in the LREE-dominated deposit. These binding mechanisms are also observed in Y-sorbed birnessite prepared at different ionic strengths. Therefore, different binding mechanisms of Y and HREE sorption on birnessite together with its preferential adsorption of HREE not only are responsible for the formation of HREE-dominated deposits from LREE-enriched granites but have important implications for the sustainable development of regolith-hosted REE deposits.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".